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Competencies: Understand existing quantum key distribution (QKD) protocols, networks and systems. Able to perform resource placement optimization in computer/communication networks. Proficient in technical
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knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and
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-cloud computation offloading algorithms. Set up network testbeds integrating hardware, software, and communication protocols to validate edge-only, cloud-only, and edge-cloud computation offloading
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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28 Feb 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Engineering Engineering Researcher Profile First Stage Researcher (R1
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the Project PI. ii. Meeting the deliverables by carrying out the computational simulations and experimental studies planned for under the scope of work of the projects within the timeframe to meet the
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Apr 2026 - 00:00 (UTC) Country Singapore Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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of final year projects (FYP) or capstone projects students under the Project PI. Meeting the deliverables by carrying out the computational simulations and experimental studies planned for under the scope
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the Infocomm Technology cluster at SIT. This project addresses the critical challenge of delivering real-time Artificial Intelligence (AI) services in Internet of Things (IoT) networks, where latency and
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that are relevant to industry demands while working on research projects in SIT. The Future Ship and System Design (FSSD) programme aims to develop strategic and innovative design capabilities for the maritime